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SafetyEye SE-ASF-132/M2KU - Video analytics server

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SafetyEye SE-ASF-132/M2KU - Video analytics server
SafetyEye SE-ASF-132/M2KU - Video analytics server
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  • Processor: Hygon 3185 — optimized for analytics workloads.
  • Memory: 16 GB — stable operation across multiple video streams.
  • Storage: 240 GB — fast and efficient data access.
  • Analytics: supports 32 video channels with 99% face recognition accuracy.
  • Power Supply: dual 550 W modules for redundancy and reliability.
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Description SafetyEye SE-ASF-132/M2KU - Video analytics server

SafetyEye SE-ASF-132/M2KU is a professional video analytics server designed for high-precision security, facial recognition, and vehicle analysis. It combines reliability, performance, and efficiency to deliver real-time intelligent analytics for modern surveillance systems.

⚙️ Optimized Performance

Powered by a Hygon 3185 processor and 16 GB RAM, the server ensures stable and responsive operation during continuous video stream analysis. It can efficiently handle dozens of simultaneous video channels with minimal latency.

💾 Efficient Storage System

The unit is equipped with a 240 GB drive designed for fast data read/write operations, enabling quick access to recognition results and high system responsiveness.

🧠 Advanced Analytics Capabilities

SafetyEye SE-ASF-132/M2KU supports a wide range of AI-powered analytics:

  • Vehicle analysis: detects vehicle type, color, brand, license plate, and behavioral attributes (seatbelt use, mobile phone, visor); accuracy — 85%.
  • Facial recognition: up to 160 images per second with 99% accuracy, supports up to 32 video channels (2 MP).
  • Human body analysis: determines gender, age group, clothing, movement speed and direction, mask presence, and object carrying.

The system can store up to 1 million faces in watch lists, making it suitable for enterprise and city-scale analytics applications.

🔌 Connectivity and Interfaces

The server provides flexible integration options:

  • 4 × 1GbE network ports;
  • 2 × USB 2.0 and 4 × USB 3.0 ports;
  • 1 × VGA output for monitoring;
  • 2 × 550 W power supplies for redundancy.

🌡️ Stability and Efficiency

Operating on CentOS, the server delivers reliable and secure performance. With redundant power and low power consumption, it maintains continuous operation even under demanding workloads.

🏗️ Compact Rack Design

The 1U rackmount chassis (439 × 631 × 44 mm) provides easy installation in server racks. The device weighs 12 kg (packaged — 16 kg), ensuring easy transport and setup.

Characteristics SafetyEye SE-ASF-132/M2KU - Video analytics server
Processor
Hygon3185 – 1 pc.
RAM
16 GB
Storage system
240 GB hard drive - 1 pc.
Graphics adapter
KT2 card – 1 pc.
Power consumption
550 W – 2 pcs.
Operating system
СentOS
Dimensions
439 × 631 × 44 mm / Rack 1U
Interfaces
Network - 1000 M - 4 ports / USB 2.0 - 2 ports / USB 3.0 - 4 ports / VGA - 1 port
Weight
12 kg
Weight with packaging
16 kg
Analytics
Structured analysis
Analysis of human bodies and vehicles in photographs and real-time video / Analysis of vehicle images – 80 images per second (2 MP) / Analysis of vehicles from video – 32 channels (2 MP) / Human body features – Direction of movement/size/speed, type/color of coat/pants, age group, hairstyle, gender, presence of a backpack, mask, whether carrying items, riding a horse, type of riding, number of people riding / Vehicle characteristics – type, color, brand, license plate number
Face recognition
Detection, recognition, and modeling of faces in photos and videos in real time / Analysis and comparison of facial images – 160 images per second / Analysis and comparison of faces from videos – 32 channels (2 MP) / Detection of facial attributes – smile, wearing a mask, wearing sunglasses, gender, age group / Recognition accuracy – 99% / Number of faces in wanted lists – 1 million / Vehicle attributes – vehicle detection, vehicle modeling, vehicle attribute analysis, vehicle recognition / Behavior analysis – seat belt fastened, sun visor open, mobile phone use
Vehicle analysis
Vehicle image analysis and comparison – 58 images per second / Vehicle attribute recognition accuracy – 85%
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